Machine learning model that estimates public-supply deliveries for domestic and other use types
This child item describes a public-supply delivery machine learning model that was developed to estimate public-supply deliveries. Publicly supplied water may be delivered to domestic users or to commercial, industrial, institutional, and irrigation (CII) users. This model predicts total, domestic, and CII per capita rates for public-supply water service areas within the conterminous United States for 2009-2020. This child item contains model input datasets, code used to build the delivery machine learning model, and national predictions. This dataset is part of a larger data release using machine learning to predict public-supply water use for 12-digit hydrologic units from 2000-2020.
This page includes the following file:
delivery_water_use_model.zip - a zip file containing input datasets, scripts, and output datasets for the delivery water use machine learning model
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"010:12"
]
|
| contactPoint |
{
"fn": "Joshua D. Larsen",
"@type": "vcard:Contact",
"hasEmail": "mailto:jlarsen@usgs.gov"
}
|
| description | This child item describes a public-supply delivery machine learning model that was developed to estimate public-supply deliveries. Publicly supplied water may be delivered to domestic users or to commercial, industrial, institutional, and irrigation (CII) users. This model predicts total, domestic, and CII per capita rates for public-supply water service areas within the conterminous United States for 2009-2020. This child item contains model input datasets, code used to build the delivery machine learning model, and national predictions. This dataset is part of a larger data release using machine learning to predict public-supply water use for 12-digit hydrologic units from 2000-2020. This page includes the following file: delivery_water_use_model.zip - a zip file containing input datasets, scripts, and output datasets for the delivery water use machine learning model |
| distribution |
[
{
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"title": "Digital Data",
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"accessURL": "https://doi.org/10.5066/P9FUL880",
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"title": "Original Metadata",
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"downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.63c6fce9d34e92aad3d120f1.xml"
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|
| identifier | http://datainventory.doi.gov/id/dataset/USGS_63c6fce9d34e92aad3d120f1 |
| keyword |
[
"Alabama",
"Arizona",
"Arkansas",
"California",
"Colorado",
"Connecticut",
"Delaware",
"District of Columbia",
"Florida",
"Georgia",
"Idaho",
"Illinois",
"Indiana",
"Iowa",
"Kansas",
"Kentucky",
"Louisiana",
"Maine",
"Maryland",
"Massachusetts",
"Michigan",
"Minnesota",
"Mississippi",
"Missouri",
"Montana",
"Nebraska",
"Nevada",
"New Hampshire",
"New Jersey",
"New Mexico",
"New York",
"North Carolina",
"North Dakota",
"Ohio",
"Oklahoma",
"Oregon",
"Pennsylvania",
"Rhode Island",
"South Carolina",
"South Dakota",
"Tennessee",
"Texas",
"USGS:63c6fce9d34e92aad3d120f1",
"Utah",
"Vermont",
"Virginia",
"Washington",
"West Virginia",
"Wisconsin",
"Wyoming",
"conterminous United States",
"modeling",
"public supply",
"water use"
]
|
| modified | 2024-08-27T00:00:00Z |
| publisher |
{
"name": "U.S. Geological Survey",
"@type": "org:Organization"
}
|
| spatial | -126.2000, 24.2000, -64.3000, 50.2000 |
| theme |
[
"Geospatial"
]
|
| title | Machine learning model that estimates public-supply deliveries for domestic and other use types |
